Job Description
We are seeking a Data Engineer to design, build, and maintain scalable data pipelines, datasets, and automation systems that support cloud cost visibility, attribution, and performance insights.

This role will work with large-scale telemetry, usage, and financial data to help Product, Engineering, and Finance stakeholders make informed, cost-aware decisions. The idóneo candidate has strong hands-on experience with cloud data engineering, AWS, Snowflake, production pipeline ownership, data quality, and performance and cost optimization.

Key Responsibilities
- Design, build, and maintain reliable end-to-end ELT and ETL pipelines in cloud environments.
- Build scalable datasets that support cloud cost visibility, attribution, usage analysis, and performance insights.
- Design and implement data models and ingestion frameworks for large-scale telemetry and usage data.
- Develop automation and tooling that enable cost-aware decision-making across Product, Engineering, and Finance teams.
- Optimize data pipelines and systems for performance, reliability,



and cost efficiency.
- Perform query tuning and improve storage and compute strategies.
- Build and maintain integrations with REST APIs and other data sources.
- Implement and support CI/CD processes and Infrastructure as Code.
- Ensure data quality, validation, auditability, and consistency across end-to-end data workflows.
- Monitor, troubleshoot, and resolve production pipeline failures, data inconsistencies, and performance issues.
- Partner with Engineering and Finance stakeholders on cloud cost optimization and usage-based insights.

Qualifications
Must-Have Skills
- Strong data engineering foundation with proven experience building and maintaining end-to-end ELT or ETL pipelines in cloud environments.
- Strong SQL and Python skills.
- Experience with data workflow and orchestration tools such as dbt, Airflow, or Dagster.
- Hands-on experience with the AWS data ecosystem, including AWS Glue, Amazon

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